Urology

A tandem reinforcement learning framework for localized prostate cancer treatment planning and machine parameter optimization.

BACKGROUND: Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) is a complex, high-dimensional problem typically solved with inverse planning solutions that are both temporally and computationally expensive. While machine learning techniques have been explored to automate this process, they often supplement rather than replace conventional optimizers and are fundamentally ...

A segmentation method with a large vision model for magnetic resonance imaging-guided adaptive radiotherapy.

BACKGROUND: Segmentation is the most effort-consuming step for magnetic resonance imaging guided adaptive radiotherapy (MRIgART). Although the segment anything model (SAM) exhibits impressive capabilities, its application in medical imaging necessitates clicks, bounding boxes, or providing mask prompts on each target image, which would still require complex human interactions. PURPOSE: This study ...

Machine learning model for fast prediction and uncertainty quantification of needle deflection during prostate biopsy.

BACKGROUND: Accurate needle placement is essential for prostate biopsy. Recently, transperineal prostate biopsies are receiving renewed interest due t...

A comprehensive analysis reveals the molecular mechanisms linking preservatives to prostate cancer risk.

BACKGROUND: Preservatives, widely used in food and skincare products, may influence prostate cancer (PCa) development. This study explores the effects...

Development of an interpretable machine learning model for predicting 4-year chronic kidney disease risk in elderly hypertensive patients.

INTRODUCTION: Age and hypertension are key drivers of renal impairment, predisposing older hypertensive adults to faster kidney function decline and h...

C-X-C Motif Chemokine Ligand 3 as a Potential Biomarker for Diagnosis and Prognosis of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the primary cause of end-stage renal disease globally, yet reliable biomarkers for its diagnosis and progression asse...

Monocyte-to-HDL ratio (MHR) is associated with overall and renal mortality in community-dwelling older individuals with chronic kidney disease (CKD).

Early Implications for Solid Organ Transplantation With the Use of Artificial Intelligence From a Bibliometric Perspective.

Artificial intelligence (AI) is increasingly transforming health care, particularly in solid organ transplantation, where it addresses complex challen...

Machine Learning Predictions for Assessing Hard-to-Place Deceased Donor Kidneys.

RATIONALE & OBJECTIVE: Nearly 20% of deceased donor kidneys in the United States are placed "out-of-sequence" (ie, outside of standard allocation rule...

Characterizing the Immune Cell Infiltration in Renal Interstitium and Therapeutic Targets of Drugs in Diabetic Nephropathy by Multiomics Study.

BACKGROUND: Immune cell infiltration in the renal interstitium contributes to the progression of diabetic nephropathy (DN), yet the precise mechanisms...

Development of a quantitative multiparametric ultrasound and deep learning classifier for the detection of prostate cancer.

OBJECTIVES: Prostate cancer (PCa) diagnosis is increasingly guided by imaging, with ultrasound (US) emerging as a cost-effective and widely accessible...

Artificial intelligence versus classical scoring systems: a comparative analysis of stone-free prediction after percutaneous nephrolithotomy.

This study aimed to compare the predictive performance of traditional stone scoring systems with a large language model based on ChatGPT in estimating...

Raman spectroscopy with machine-learning classification for the prediction of stereotactic radiotherapy induced treatment toxicity in high-risk localised prostate cancer.

Radiotherapy can lead to late-onset toxicity, to varying extents between individuals due to differences in radiosensitivity. Predicting which patients...

From prostate-specific antigen to precision: The future of prostate cancer diagnosis with artificial intelligence, biomarkers, and imaging.

BACKGROUND: Prostate cancer (PCa) diagnosis has historically relied on prostate-specific antigen (PSA) testing. Although PSA screening significantly r...

From ChatGPT to UroGPT: A guideline-trained artificial intelligence model for male infertility.

BACKGROUND: ChatGPT is not yet sufficiently reliable for answering clinical questions relevant to direct patient care. We hypothesized that a GPT mode...

Childhood dyslexia risk elevated by heavy metal mixtures from e-waste: A machine learning-driven mixture modeling study.

Environmental heavy metal mixtures from informal e-waste recycling are potential neurotoxicants, but their link to developmental dyslexia remains uncl...

Frailty trajectories and risk of incident advanced CKM syndrome: A national cohort analysis.

BACKGROUND: The interplay between frailty dynamics and the newly defined Cardiovascular-Kidney-Metabolic (CKM) syndrome remains poorly understood. We ...

Ultrasound-Based Kidney Stone Classification Using Kronecker Self-Organizing Map Forward Harmonic Network.

Kidney stone disease is a prevalent urological disorder that can result in severe pain, obstruction, and long-term complications if not detected and m...

Refining deep learning segmentation in gallium-68-prostate-specific membrane antigen-11 positron emission tomography: evaluation of small lesion filtering and intersection-over-union thresholds.

PURPOSE: Evaluate how small lesion filtering and different intersection-over-union (IoU) thresholds influence deep learning segmentation of Ga-68-PSMA...

Organ preservation in rectal cancer: an endoscopist's perspective on current evidence and future directions.

Rectal cancer management has increasingly shifted toward organ-preserving strategies that aim to maintain oncologic control while preserving bowel, ur...